Transforming retail for sustainable future: modelling key drivers of AI adoption for sustainable retailing to optimise supply chain and reduce environmental impact

The incorporation of artificial intelligence (AI) into the retail industry is revolutionising sustainability practices, increasing efficiency, and stimulating innovation. This article investigates the use of AI in retail, with a particular emphasis on its role in promoting sustainability. Fifteen key drivers were identified through a review of the literature. Interpretive structural modelling (ISM) and MICMAC analysis were then employed to examine the relationships between these drivers. Finally, the analytic hierarchy process (AHP) was used to rank them. The results reveal that 'blockchain and AI integration' (AI1) and 'data analytics and machine learning' (AI3) are the most critical drivers for AI adoption in the retail sector. Retailers should prioritise these two drivers, as they possess the highest driving power and are pivotal in influencing AI adoption. The findings offer useful insights for retailers looking to balance profitability and environmental responsibility, as well as a foundation for future AI applications in the context of sustainable business practices. The implications for policymakers and stakeholders in promoting sustainable retailing with AI have also been addressed.